Utilizing river and wastewater as a SARS-CoV-2 surveillance tool to predict trends and identify variants of concern in settings with limited formal sewage systems.


Journal

Research square
Titre abrégé: Res Sq
Pays: United States
ID NLM: 101768035

Informations de publication

Date de publication:
14 Apr 2023
Historique:
pubmed: 24 4 2023
medline: 24 4 2023
entrez: 24 04 2023
Statut: epublish

Résumé

The COVID-19 pandemic continues to impact health systems globally and robust surveillance is critical for pandemic control, however not all countries can sustain community surveillance programs. Wastewater surveillance has proven valuable in high-income settings, but little is known about how river and informal sewage in low-income countries can be used for environmental surveillance of SARS-CoV-2. In Malawi, a country with limited community-based COVID-19 testing capacity, we explored the utility of rivers and wastewater for SARS-CoV-2 surveillance. From May 2020 - January 2022, we collected water from up to 112 river or informal sewage sites/month, detecting SARS-CoV-2 in 8.3% of samples. Peak SARS-CoV-2 detection in water samples predated peaks in clinical cases. Sequencing of water samples identified the Beta, Delta, and Omicron variants, with Delta and Omicron detected well in advance of detection in patients. Our work highlights wastewater can be used for detecting emerging waves, identifying variants of concern and function as an early warning system in settings with no formal sewage systems.

Identifiants

pubmed: 37090541
doi: 10.21203/rs.3.rs-2801767/v1
pmc: PMC10120776
pii:
doi:

Types de publication

Preprint

Langues

eng

Subventions

Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : FIC NIH HHS
ID : K01 TW010853
Pays : United States

Commentaires et corrections

Type : UpdateIn

Auteurs

Kayla Barnes (K)

Harvard TH Chan School of Public Health.

Joshua Levy (J)

Scripps Research Institute.

Kristian Andersen (K)

Department of Immunology and Microbiology The Scripps Research Institute La Jolla CA USA.

Jillian Gauld (J)

Institute for Disease Modeling, Bill & Melinda Gates Foundation.

Jonathan Rigby (J)

Department of Clinical Sciences, Liverpool School of Tropical Medicine.

Oscar Kanjerwa (O)

Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi.

Chisomo Chilupsya (C)

Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences, Blantyre, Malawi.

Catherine Anscombe (C)

Malawi-Liverpool-Wellcome Trust Clinical Research Programme.

Omar Mbeti (O)

Blantyre District Health Office.

Edward Cairns (E)

Department of Evolution, Ecology and Behaviour, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool.

Herbert Thole (H)

Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences.

Shannon McSweeney (S)

Department of Clinical Sciences, Liverpool School of Tropical Medicine.

Marah Chibwana (M)

Malawi-Liverpool-Wellcome Clinical Research Programme, Kamuzu University of Health Sciences.

Philip Ashton (P)

Malawi Liverpool Wellcome.

John Meschke (J)

University of Washington.

Peter Diggle (P)

Lancaster University.

Jennifer Cornick (J)

Department of Evolution, Ecology and Behaviour, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool.

Kondwani Jambo (K)

Liverpool School of Tropical Medicine.

Gift Kawalazira (G)

Blantyre District Health Office.

Steve Paterson (S)

University of Liverpool.

Tonney Nyirenda (T)

Department of Pathology, Kamuzu University of Health Sciences.

Nicholas Feasey (N)

Liverpool School of Tropical Medicine.

Benjamin Chilima (B)

Public Health Institute of Malawi.

Classifications MeSH